diff --git a/python/paddle/fluid/tests/unittests/mkldnn/test_requantize_mkldnn_op.py b/python/paddle/fluid/tests/unittests/mkldnn/test_requantize_mkldnn_op.py
index 4a48453da5290888867bb933b3c8753a70d6f65a..750e7f37df4bff34006f34ff52292bfc621a75fc 100644
--- a/python/paddle/fluid/tests/unittests/mkldnn/test_requantize_mkldnn_op.py
+++ b/python/paddle/fluid/tests/unittests/mkldnn/test_requantize_mkldnn_op.py
@@ -16,6 +16,8 @@ from __future__ import print_function
 
 import unittest
 import numpy as np
+import paddle.fluid as fluid
+import paddle.fluid.core as core
 from paddle.fluid.tests.unittests.op_test import OpTest
 from mkldnn_op_test import format_reorder
 
@@ -25,29 +27,31 @@ class TestReQuantizeOp(OpTest):
         self.op_type = 'requantize'
         self.scale_in = 2.0
         self.scale_out = 1.5
-        self.input_size = [1, 1, 5, 5]
+        self.input_size = [1, 1, 10, 10]
         self.data_type = 'int8'
         self.set_scale()
         self.set_data_type()
+        self.prepare_inputs()
 
+    def prepare_inputs(self):
         scale_shift = self.scale_out / self.scale_in
 
         if self.data_type == 'int8':
-            input = (np.random.randint(0, 100, self.input_size) - 50
-                     ).astype(self.data_type)
-            output_tmp = np.round(input.astype('float32') *
+            self.input = (np.random.randint(0, 100, self.input_size) - 50
+                          ).astype(self.data_type)
+            output_tmp = np.round(self.input.astype('float32') *
                                   scale_shift).astype('int8')
         else:
-            input = (np.random.randint(0, 100,
-                                       self.input_size)).astype(self.data_type)
-            output_tmp = np.round(input.astype('float32') *
+            self.input = (np.random.randint(
+                0, 100, self.input_size)).astype(self.data_type)
+            output_tmp = np.round(self.input.astype('float32') *
                                   scale_shift).astype('uint8')
 
-        output = format_reorder(output_tmp, self.input_size)
+        self.output = format_reorder(output_tmp, self.input_size)
 
-        self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
+        self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(self.input)}
 
-        self.outputs = {'Output': output}
+        self.outputs = {'Output': self.output}
 
         self.attrs = {'Scale_in': self.scale_in, 'Scale_out': self.scale_out}
 
@@ -90,5 +94,48 @@ class TestReQuantizeOp4(TestReQuantizeOp2):
         self.data_type = 'uint8'
 
 
+#-------------------test reused requantize op---------------------------
+
+
+class TestReQuantizeOpReused(TestReQuantizeOp):
+    def setUp(self):
+        self.input_size = [1, 1, 10, 10]
+        self.data_type = 'int8'
+        self.set_scale()
+        self.prepare_inputs()
+
+    def set_scale(self):
+        self.scale_in = 0.1
+        self.scale_out = 0.2
+
+    def test_check_output(self):
+        variables = {
+            "input": self.input,
+            "output": self.output,
+        }
+        program = fluid.Program()
+        with fluid.program_guard(program):
+            block = program.global_block()
+            for name in variables:
+                block.create_var(
+                    name=name, dtype="int8", shape=variables[name].shape)
+            requant_op = block.append_op(
+                type="requantize",
+                inputs={'Input': block.var('input'), },
+                outputs={"Output": block.var('output')},
+                attrs={'Scale_in': self.scale_in,
+                       'Scale_out': self.scale_out})
+            place = core.CPUPlace()
+            exe = fluid.Executor(place)
+            for i in range(2):
+                out = exe.run(program,
+                              feed={'input': variables['input']},
+                              fetch_list=['output'])
+
+            self.assertTrue(
+                np.allclose(
+                    variables['output'], out[0], atol=1e-4), 'output')
+
+
 if __name__ == '__main__':
     unittest.main()